Salicylic acid-mediated alleviation of salt stress: Insights from physiological and transcriptomic analysis in Asarum sieboldii Miq.

As global agriculture faces the pressing threat of salt stress, innovative solutions are imperative for sustainable agriculture. The remarkable potential of salicylic acid (SA) in enhancing plant resilience against environmental stressors has recently gained attention. However, the specific molecular mechanisms by which SA mitigates salt stress in Asarum sieboldii Miq., a valuable medicinal plant, remain poorly understood. Here, we evaluated the physiological and transcriptomic regulatory responses of A. sieboldii under salt stress (100 mM NaCl), both in the presence (1 mM SA) and absence of exogenous SA. The results highlighted that SA significantly alleviates salt stress, primarily through enhancing antioxidant activities as evidenced by increased superoxide dismutase, and peroxidase activities. Additionally, we observed an increment in chlorophyll (a and b), proline, total soluble sugar, and plant fresh weight, along with a decrease in malondialdehyde contents. Transcriptome analysis suggested consistency in the regulation of many differentially expressed genes and transcription factors (TFs); however, genes targets (GSTs, TIR1, and NPR1), and TFs (MYB, WRKY, TCP, and bHLH) possessed expressional uniqueness, and majority had significantly up-regulated trends in SA-coupled salt stress treatments. Further, bioinformatics and KEGG enrichment analysis indicated several SA-induced significantly enriched biological pathways. Specifically, plant hormone signal transduction was identified as being populated with key genes distinctive to auxin, cytokinin, ethylene, and salicylic acid signaling, suggesting their important role in salt stress alleviation. Inclusively, this report presents a comprehensive analysis encompassing gene targets, TFs, and biological pathways, and these insights may offer a valuable contribution to our knowledge of SA-mediated regulation and its crucial role in enhancing plant defense against diverse abiotic stressors.

The influence of cooperative fermentation on the structure, crystallinity, and rheological properties of buckwheat starch.

The effects of co-fermentation of yeast and Lactiplantibacillus plantarum 104 on buckwheat starch physical properties were investigated by various analytical techniques. To investigate the regulations of starch modification during fermentation and to provide a foundation for improving the performance of modified properties of buckwheat starch food. The pasting properties were decreased by co-fermentation also resulted in a reduction in the relative crystallinity. Scanning electron microscopy (SEM) demonstrated that more holes and a relatively rough granule surface were seen in the co-fermentation group. Fourier transform-infrared spectroscopy (FT-IR) results suggested that co-fermentation fermentation decreased the degree of short-range order (DO) and degree of t1he double helix (DD). The results demonstrated that co-fermentation altered these properties more rapidly than spontaneous fermentation. In conclusion, Lactiplantibacillus plantarum 104 could be used for buckwheat fermentation to improve food quality.

SEG-LUS: A novel ultrasound segmentation method for liver and its accessory structures based on muti-head self-attention.

Although liver ultrasound (US) is quick and convenient, it presents challenges due to patient variations. Previous research has predominantly focused on computer-aided diagnosis (CAD), particularly for disease analysis. However, characterizing liver US images is complex due to structural diversity and a limited number of samples. Normal liver US images are crucial, especially for standard section diagnosis. This study explicitly addresses Liver US standard sections (LUSS) and involves detailed labeling of eight anatomical structures. We propose SEG-LUS, a US image segmentation model for the liver and its accessory structures. In SEG-LUS, we have adopted the shifted windows feature encoder combined with the cross-attention mechanism to adapt to capturing image information at different scales and resolutions and address context mismatch and sample imbalance in the segmentation task. By introducing the UUF module, we achieve the perfect fusion of shallow and deep information, making the information retained by the network in the feature extraction process more comprehensive. We have improved the Focal Loss to tackle the imbalance of pixel-level distribution. The results show that the SEG-LUS model exhibits significant performance improvement, with mPA, mDice, mIOU, and mASD reaching 85.05%, 82.60%, 74.92%, and 0.31, respectively. Compared with seven state-of-the-art semantic segmentation methods, the mPA improves by 5.32%. SEG-LUS is positioned to serve as a crucial reference for research in computer-aided modeling using liver US images, thereby advancing the field of US medicine research.

FHUSP-NET: A Multi-task model for fetal heart ultrasound standard plane recognition and key anatomical structures detection.

In prenatal ultrasound screening, rapid and accurate recognition of the fetal heart ultrasound standard planes(FHUSPs) can more objectively predict fetal heart growth. However, the small size and movement of the fetal heart make this process more difficult. Therefore, we design a deep learning-based FHUSP recognition network (FHUSP-NET), which can automatically recognize the five FHUSPs and detect tiny key anatomical structures at the same time. 3360 ultrasound images of five FHUSPs from 1300 mid-pregnancy pregnant women are included in this study. 10 fetal heart key anatomical structures are manually annotated by experts. We apply spatial pyramid pooling with a fully connected spatial pyramid convolution module to capture information about targets and scenes of different sizes as well as improve the perceptual ability and feature representation of the model. Additionally, we adopt the squeeze-and-excitation networks to improve the sensitivity of the model to the channel features. We also introduce a new loss function, the efficient IOU loss, which makes the model effective for optimizing similarity. The results demonstrate the superiority of FHUSP-NET in detecting fetal heart key anatomical structures and recognizing FHUSPs. In the detection task, the value of mAP@0.5, precision, and recall are 0.955, 0.958, and 0.931, respectively, while the accuracy reaches 0.964 in the recognition task. Furthermore, it takes only 13.6 ms to detect and recognize one FHUSP image. This method helps to improve ultrasonographers' quality control of the fetal heart ultrasound standard plane and aids in the identification of fetal heart structures in a less experienced group of physicians.

[Exploration of transcriptome SSR markers and its application in genetic diversity assessment of Asarum sieboldii].

To explore the genetic diversity of Asarum sieboldii this study developed SSR markers based on transcriptome sequencing results and five populations of A.sieboldii from different regions were used as samples for genetic diversity assessment using software such as GenALEx 6.5, NTSYS 2.1, and Structure 2.3.4. The results showed that 16 SSR markers with high polymorphism and good repeatability were selected from the A.sieboldii transcriptome. Primers designed based on the flanking sequences of these markers successfully amplified 56 polymorphic fragments from 150 individual samples of the five A.sieboldii populations. On average, each primer amplified 3.5 polymorphic fragments, ranging from 2 to 8. The mean values of expected heterozygosity(H_e), Shannon's diversity index(I), Nei's gene diversity index(H), and the polymorphic information content(PIC) were 0.172, 0.281, 0.429, and 0.382, respectively. The mean population differentiation coefficient(F_(ST)) was 0.588, consistent with the analysis of molecular variance(AMOVA) results, which indicated greater genetic variation among A.sieboldii populations(69%) than that within populations(31%). The percentage of polymorphic loci(PPL) ranged from highest to lowest as SNJ>LN>SY>SZ>TB. Principal coordinate analysis(PCoA) and UPGMA clustering analysis further revealed genetic clustering of A.sieboldii individuals based on their geographical distribution, consistent with the results of the structure clustering analysis. In summary, the SSR markers developed from the transcriptome effectively assessed the genetic differentiation and population structure of natural A.sieboldii populations, revealing a relatively low genetic diversity in A.sieboldii, with genetic variation primarily observed at the population level and a correlation between population differentiation and geographic distance.

Caffeoyl-coenzyme A O-methyltransferase mediates regulation of carbon flux fluctuations during phenylpropenes and lignin biosynthesis in the vegetative organ roots of Asarum sieboldii Miq.

Asarum sieboldii Miq. possesses remarkable medicinal value due to its essential oil enriched with phenylpropenes (e.g., methyleugenol and safrole). Although the biosynthesis of phenylpropenes shares a common pathway with lignin, the regulation mechanisms in carbon flux allocation between them are unclear. This study is the first to genetically verify the carbon flux regulation mechanism in A. sieboldii roots. We regulated the expression of Caffeoyl-coenzyme A O-methyltransferase (CCoAOMT), an essential enzyme in the common pathway, to investigate carbon flux allocation in vegetative organs. Here, the lignin and phenylpropene content fluctuation was analyzed by wet chemistry and GC-MS methods. A bona fide CCoAOMT gene from A. sieboldii was firstly cloned and verified. Preliminary heterologous expression validation in transgenic Arabidopsis thaliana showed that RNAi-induced CCoAOMT down-regulation significantly decreased lignin content by 24% and increased the S/G ratio by 30%; however, AsCCoAOMT over-expression in A. thaliana resulted in a 40% increase in lignin content and a 20% decrease in the S/G ratio when compared to the wild type. Similar trends were noted in homologous transformation in A. sieboldii, although the variations were not conspicuous. Nevertheless, the transgenic A. sieboldii plants displayed substantial differences in the level of phenylpropene compounds methyleugenol and safrole leading to a 168% increase in the methyleugenol/safrole ratio in the over-expression line and a 73% reduction in RNAi-suppression line. These findings suggest that the biosynthesis of phenylpropene constituents methyleugenol and safrole seems to be prioritized over lignin. Furthermore, this study indicated that suppression of AsCCoAOMT resulted in marked root susceptibility to pathogenic fungal disease, implying a significant additional role of CCoAOMT in protecting plant vegetative parts from diseases. Overall, the present study provides important references and suggests that future research should be aimed at elucidating the detailed mechanisms of the carbon flux allocation between phenylpropenes and lignin biosynthesis, as well as the disease resistance competency.

Prevention of High-Fat-Diet-Induced Dyslipidemia by Lactobacillus plantarum LP104 through Mediating Bile Acid Enterohepatic Axis Circulation and Intestinal Flora.

This work aimed to investigate the alleviative mechanism of Lactobacillus plantarum LP104 (LP104) isolated from kimchi on high-fat-diet-induced dyslipidemia by targeting the intestinal flora and bile acid (BA) metabolism. Oral administration of LP104 over 8 weeks reduced body weight gain and body fat, as well as ameliorating serum and hepatic dyslipidemia in HFD-fed C57BL/6N mice significantly. LP104 intervention also increased the ileal tauro-α/ß-muricholic acid sodium salt (T-α-MCA or T-ß-MCA) and tauroursodeoxycholic acid (TUDCA) concentrations to suppress the enterohepatic farnesoid X receptor/fibroblast growth factor 15-fibroblast growth factor receptor 4 (FXR/FGF15-FGFR4) signaling pathway, which stimulated the hepatic cholic acid (CA) and chenodeoxycholic acid (CDCA) de novo synthesis through using cholesterol. Then, LP104 treatment accelerated BA excretion with the feces and cholesterol efflux to improve HFD-caused hyperlipidemia effectively. The 16S rRNA gene high-throughput sequencing revealed that LP104 promoted intestinal flora rebalance by increasing the abundances of Bacteroides, Akkermansia, Lactobacillus, and Clostridium and decreasing the abundance of Oscillospira and Coprococcus. Meanwhile, Spearman correlation analysis demonstrated that the differential flora were closely related to BA signaling molecules including CA, CDCA, T-α-MCA, T-ß-MCA, and TUDCA after LP104 intervention. These findings provided new evidence that LP104 had the potential to be used as a naturally functional food for the prevention of dyslipidemia.

Simulation-to-real generalization for deep-learning-based refraction-corrected ultrasound tomography image reconstruction.

Objective. The image reconstruction of ultrasound computed tomography is computationally expensive with conventional iterative methods. The fully learned direct deep learning reconstruction is promising to speed up image reconstruction significantly. However, for direct reconstruction from measurement data, due to the lack of real labeled data, the neural network is usually trained on a simulation dataset and shows poor performance on real data because of the simulation-to-real gap.Approach. To improve the simulation-to-real generalization of neural networks, a series of strategies are developed including a Fourier-transform-integrated neural network, measurement-domain data augmentation methods, and a self-supervised-learning-based patch-wise preprocessing neural network. Our strategies are evaluated on both the simulation dataset and real measurement datasets from two different prototype machines.Main results. The experimental results show that our deep learning methods help to improve the neural networks' robustness against noise and the generalizability to real measurement data.Significance. Our methods prove that it is possible for neural networks to achieve superior performance to traditional iterative reconstruction algorithms in imaging quality and allow for real-time 2D-image reconstruction. This study helps pave the path for the application of deep learning methods to practical ultrasound tomography image reconstruction based on simulation datasets.

The ameliorative effect of probiotics on diet-induced lipid metabolism disorders: A review.

High-fat diet induces lipid metabolism disorders that has become one of the grievous public health problems and imposes a serious economic and social burden worldwide. Safety probiotics isolated from nature are regarded as a novel supplementary strategy for preventing and improving diet-induced lipid metabolism disorders and related chronic diseases. The present review summarized the latest researches of probiotics in high fat diet induced lipid metabolism disorders to provide a critical perspective on the regulatory function of probiotics for future research. Furthermore, the screening criteria and general sources of probiotics with lipid-lowering ability also outlined to enlarge microbial species resource bank instantly, which promoted the development of functional foods with lipid-lowering strains from nature. After critically reviewing the lipid-lowering potential of probiotics both in vitro and in vivo and even in clinical data of humans, we provided a perspective that probiotics activated AMPK signaling pathway to regulate fat synthesis and decomposition, as well as affected positively the gut microbiota structure, intestinal barrier function and systemic inflammatory response, then these beneficial effects are amplified along Gut-liver axis, which regulated intestinal flora metabolites such as SCFAs and BAs by HMGCR/FXR/SHP signaling pathway to improve high fat diet induced lipid metabolism disorders effectively.

The impact of circadian rhythms on the immune response to influenza vaccination in middle-aged and older adults (IMPROVE): a randomised controlled trial.

BACKGROUND: Vaccination is important in influenza prevention but the immune response wanes with age. The circadian nature of the immune system suggests that adjusting the time of vaccination may provide an opportunity to improve immunogenicity. Our previous cluster trial in Birmingham suggested differences between morning and afternoon vaccination for some strains in the influenza vaccine in older adults. Whether this effect is also seen in a younger age group with less likelihood of compromised immunity is unknown. We therefore conducted an individual-based randomized controlled trial in Guangzhou to test the hypothesis that influenza vaccination in the morning induces a stronger immune response in older adults than afternoon vaccination. We included adults in middle age to determine if the effect was also seen in younger age groups. RESULTS: Of the 418 participants randomised, 389 (93.1%, 191 middle-aged adults aged 50-60 years and 198 older adults aged 65-75 years) were followed up. Overall, there was no significant difference between the antibody titers (geometric mean /95% CI) after morning vs afternoon vaccination (A/H1N1: 39.9 (32.4, 49.1) vs. 33.0 (26.7, 40.7), p = 0.178; A/H3N2: 92.2 (82.8, 102.7) vs. 82.0 (73.8, 91.2), p = 0.091; B: 15.8 (13.9, 17.9) vs. 14.4 (12.8, 16.3), p = 0.092), respectively. However, in pre-specified subgroup analyses, post-vaccination titers for morning versus afternoon vaccination in the 65-75 years subgroup were (A/H1N1): 49.5 (36.7, 66.6) vs. 32.9 (24.7, 43.9), p = 0.050; (A/H3N2): 93.5 (80.6, 108.5) vs. 73.1 (62.9, 84.9), p = 0.021; (B): 16.6 (13.8, 20.1) vs. 14.4 (12.3, 17.0), p = 0.095, respectively. Among females, antibody titers for morning versus afternoon vaccination were (A/H1N1): 46.9 (35.6, 61.8) vs. 31.1 (23.8, 40.7), p = 0.030; (A/H3N2): 96.0 (83.5, 110.3) vs. 84.7 (74.4, 96.5), p = 0.176; (B): 14.8 (12.7, 17.3) vs. 13.0 (11.3, 14.9), p = 0.061, respectively. In the 50-60 years old subgroup and males, there were no significant differences between morning and afternoon vaccination. CONCLUSIONS: Morning vaccination may enhance the immunogenicity to influenza vaccine in adults aged over 65 and women. An intervention to modify vaccination programs to vaccinate older individuals in the morning is simple, cost free and feasible in most health systems.

Ameliorative effect of Lactobacillus plantarum Lp2 against cyclophosphamide-induced liver injury in mice.

Cyclophosphamide (CTX) is a widely used anticancer drug that can cause liver injury, but there is no effective treatment available at present. The antioxidant properties of Lactobacillus plantarum Lp2 in vitro and its effect on CTX-induced liver injury in mice were investigated thoroughly. The order of antioxidant capacity of the fermentate of Lp2 was as followed: fermented supernatant > cell-free extract > intact cell. BALB/c mice were intraperitoneally injected with 80 mg/kg BW/d CTX for 3 days to build a liver injury model, then treated with Lp2 fermented supernatant (Lp2-s) and Lp2 culture broth (Lp2). After 10 days, the indicators of oxidative stress and liver injury were measured. Both Lp2-s and Lp2 restored the levels of T-SOD, CAT, GSH-Px, MDA, GSH, ALT, and AST. The western blotting results showed that Lp2-s and Lp2 ameliorated CTX-induced oxidative damage and hepatocyte apoptosis via inhibiting MAPKs pathway and strengthening Nrf2/HO-1/NQO1 antioxidant defense system, thus inhibiting the mitochondrial-mediated apoptosis pathway. Therefore, both Lp2-s and Lp2 had similar protective effects on CTX-induced liver injury.

Managing energy-water-carbon-food nexus for cleaner agricultural greenhouse production: A control system approach.

Poverty, food insecurity and climate change are global issues facing humanity, threatening social, economic and environmental sustainability. Greenhouse cultivation provides a potential solution to these challenges. However, some greenhouses operate inefficiently and need to be optimized for more economical and cleaner crop production. In this paper, an economic model predictive control (EMPC) method for a greenhouse is proposed. The goal is to manage the energy-water­carbon-food nexus for cleaner production and sustainable development. First, an optimization model that minimizes the greenhouse's operating costs, including costs associated with greenhouse heating/cooling, ventilation, irrigation, carbon dioxide (CO2) supply and carbon emissions taking into account both the CO2 equivalent (CO2-eq) emissions caused by electrical energy consumption and the negative emissions caused by crop photosynthesis, is developed and solved. Then, a sensitivity analysis is carried out to study the impact of electricity price, supplied CO2 price and social cost of carbon (SCC) on the optimization results. Finally, a model predictive control (MPC) controller is designed to track the optimal temperature, relative humidity, CO2 concentration and incoming radiation power in presence of system disturbances. Simulation results show that the proposed approach increases the operating costs by R186 (R denotes the South African currency, Rand) but reduces the total cost by R827 and the carbon emissions by 1.16 tons when compared with a baseline method that minimizes operating costs only. The total cost is more sensitive to changes in SCC than that in electricity price and supplied CO2 price. The MPC controller has good tracking performance under different levels of system disturbances. Greenhouse environmental factors are kept within specified ranges suitable for crop growth, which increases crop yields. This study can provide effective guidance for growers' decision-making to achieve sustainable development goals.

Antioxidant Mechanism of Lactiplantibacillus plantarum KM1 Under H2O2 Stress by Proteomics Analysis.

Lactiplantibacillus plantarum KM1 was screened from natural fermented products, which had probiotic properties and antioxidant function. The survival rate of L. plantarum KM1 was 78.26% at 5 mM H2O2. In this study, the antioxidant mechanism of L. plantarum KM1 was deeply analyzed by using the proteomics method. The results demonstrated that a total of 112 differentially expressed proteins (DEPs) were screened, of which, 31 DEPs were upregulated and 81 were downregulated. The Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis indicated that DEPs participated in various metabolic pathways such as pyruvate metabolism, carbon metabolism, trichloroacetic acid cycle, amino acid metabolism, and microbial metabolism in diverse environments. These metabolic pathways were related to oxidative stress caused by H2O2 in L. plantarum KM1. Therefore, the antioxidant mechanism of L. plantarum KM1 under H2O2 stress provided a theoretical basis for its use as a potential natural antioxidant.

Long non-coding RNA ZFY-AS1 represses periodontitis tissue inflammation and oxidative damage via modulating microRNA-129-5p/DEAD-Box helicase 3 X-linked axis.

A large number of studies have manifested long non-coding RNA (lncRNA) is involved in the modulation of the development of periodontitis, but the specific mechanism has not been fully elucidated. The purpose of this study was to explore the biological function and latent molecular mechanism of lncZFY-AS1 in periodontitis. The results clarified lncZFY-AS1 and DEAD-Box Helicase 3 X-Linked (DDX3X) were up-regulated, but microRNA (miR)-129-5p was down-regulated in periodontitis. Knockdown of lncZFY-AS2 or overexpression of miR-129-5p decreased macrophage infiltration and periodontal membrane cell apoptosis, increased cell viability, repressed inflammatory factors and nuclear factor kappa B activation, reduced oxidative stress, but promoted nuclear factor-E2-related factor 2/heme oxygenase 1 expression. LncZFY-AS1 elevation further aggravated periodontitis inflammation, oxidative stress, and apoptosis. LncZFY competitively adsorbed miR-129-5p to mediate DDX3X expression. Knockdown lncZFY's improvement effect on periodontitis was reversed by depressive miR-129-5p or enhancive DDX3X. In conclusion, these data suggest lncZFY-AS1 promotes inflammatory injury and oxidative stress in periodontitis by competitively binding to miR-129-5p and mediating DDX3X expression. LncZFY-AS1/miR-129-5p/DDX3X may serve as a novel molecular target for treatment of periodontitis in the future.

Guaranteed Cost Finite-Time Control of Uncertain Coupled Neural Networks.

This article investigates a robust guaranteed cost finite-time control for coupled neural networks with parametric uncertainties. The parameter uncertainties are assumed to be time-varying norm bounded, which appears on the system state and input matrices. The robust guaranteed cost control laws presented in this article include both continuous feedback controllers and intermittent feedback controllers, which were rarely found in the literature. The proposed guaranteed cost finite-time control is designed in terms of a set of linear-matrix inequalities (LMIs) to steer the coupled neural networks to achieve finite-time synchronization with an upper bound of a guaranteed cost function. Furthermore, open-loop optimization problems are formulated to minimize the upper bound of the quadratic cost function and convergence time, it can obtain the optimal guaranteed cost periodically intermittent and continuous feedback control parameters. Finally, the proposed guaranteed cost periodically intermittent and continuous feedback control schemes are verified by simulations.

In Silico and In Vivo Studies on the Mechanisms of Chinese Medicine Formula (Gegen Qinlian Decoction) in the Treatment of Ulcerative Colitis.

Ulcerative colitis (UC) is a chronic inflammatory bowel disease, and Gegen Qinlian Decoction (GQD), a Chinese botanical formula, has exhibited beneficial efficacy against UC. However, the mechanisms underlying the effect of GQD still remain to be elucidated. In this study, network pharmacology approach and molecular docking in silico were applied to uncover the potential multicomponent synergetic effect and molecular mechanisms. The targets of ingredients in GQD were obtained from Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and Bioinformatics Analysis Tool for Molecular mechANism of TCM (BATMAN-TCM) database, while the UC targets were retrieved from Genecards, therapeutic target database (TTD) and Online Mendelian Inheritance in Man (OMIM) database. The topological parameters of Protein-Protein Interaction (PPI) data were used to screen the hub targets in the network. The possible mechanisms were investigated with gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Molecular docking was used to verify the binding affinity between the active compounds and hub targets. Network pharmacology analysis successfully identified 77 candidate compounds and 56 potential targets. The targets were further mapped to 20 related pathways to construct a compound-target-pathway network and an integrated network of GQD treating UC. Among these pathways, PI3K-AKT, HIF-1, VEGF, Ras, and TNF signaling pathways may exert important effects in the treatment of UC via inflammation suppression and anti-carcinogenesis. In the animal experiment, treatment with GQD and sulfasalazine (SASP) both ameliorated inflammation in UC. The proinflammatory cytokines (TNF-α, IL-1ß, and IL-6) induced by UC were significantly decreased by GQD and SASP. Moreover, the protein expression of EGFR, PI3K, and phosphorylation of AKT were reduced after GQD and SASP treatment, and there was no significance between the GQD group and SASP group. Our study systematically dissected the molecular mechanisms of GQD on the treatment of UC using network pharmacology, as well as uncovered the therapeutic effects of GQD against UC through ameliorating inflammation via downregulating EGFR/PI3K/AKT signaling pathway and the pro-inflammatory cytokines such as TNF-α, IL-1ß and IL-6.

Efficacy of herbal medicine (Gegen Qinlian Decoction) on ulcerative colitis: A systematic review of randomized controlled trials.

BACKGROUND: This systematic review aims to evaluate the efficacy of Gegen Qinlian Decoction (GQD) for ulcerative colitis (UC). METHODS: PubMed, EMBASE, Springer LINK, Cochrane Library, the China National Knowledge Infrastructure, Chongqing Weipu Database for Chinese Technical Periodicals, Wan-fang Database, and Chinese Biomedicine Database were searched from their inception to December 2018 for randomized controlled trials comparing the use of GQD alone or in combination with western medicine (WM) with that of WM therapies for UC. Outcomes on the therapy's effectiveness rate, ulcerative colitis endoscopic index of severity (UCEIS), recurrence rate, and adverse events were extracted and analyzed by Review Manager 5.3 software. Meta-analysis was combined with fixed or random-effects model, and risk ratios (RR) and 95% confidence intervals (CI) were calculated for all outcomes. Two researchers independently reviewed each trial to determine its inclusion. The Cochrane risk of bias assessment tool was used for quality assessment. RESULTS: We included 22 trials involving 2028 patients with UC. When compared with WM therapy, GQD significantly improved the clinical effectiveness (n = 591, RR = 1.21, 95% CI: 1.12-1.31, P < .00001) and recurrence rate (n = 94, RR = 0.23, 95% CI: 0.10-0.54, P = .0006). GQD plus WM was more effective in improving the clinical effectiveness (n = 1337, RR = 1.21, 95% CI: 1.16-1.27, P < .00001), and decreasing UCEIS scores (n = 384, mean difference  = -0.63, 95% CI: -1.26--0.01, P = .05), recurrence rate (n = 179, RR = 0.18, 95% CI: 0.06-0.61, P = .006). In addition, the adverse events for GQD (n = 238, RR = 0.20, 95% CI: 0.02-1.68, P = .14) and GQD plus WM (n = 427, RR = 0.37, 95% CI: 0.15-0.90, P = .03) was significantly lower than that for WM alone. Noted adverse events primarily included gastrointestinal symptoms, headache, dizziness, and leukocytopenia. CONCLUSIONS: This meta-analysis shows that GQD used alone or in combination with WM might have potential benefits in curing UC. However, there is no sufficient evidence to draw definite conclusion supporting the effect of GQD for UC due to poor methodological quality of the included trials. More rigorously designed investigations and studies with large sample sizes should be conducted to establish clinical evidence further.

Multiscale Cooperative Differential Evolution Algorithm.

A multiscale cooperative differential evolution algorithm is proposed to solve the problems of narrow search range at the early stage and slow convergence at the later stage in the performance of the traditional differential evolution algorithms. Firstly, the population structure of multipopulation mechanism is adopted so that each subpopulation is combined with a corresponding mutation strategy to ensure the individual diversity during evolution. Then, the covariance learning among populations is developed to establish a suitable rotating coordinate system for cross operation. Meanwhile, an adaptive parameter adjustment strategy is introduced to balance the population survey and convergence. Finally, the proposed algorithm is tested on the CEC 2005 benchmark function and compared with other state-of-the-art evolutionary algorithms. The experiment results showed that the proposed algorithm has better performance in solving global optimization problems than other compared algorithms.

Fuzzy entropy based on differential evolution for breast gland segmentation.

For the diagnosis and treatment of breast tumors, the automatic detection of glands is a crucial step. The true segmentation of the gland is directly related to effective treatment effect of the patient. Therefore, it is necessary to propose an automatic segmentation algorithm based on mammary gland features. A segmentation method of differential evolution (DE) fuzzy entropy based on mammary gland is proposed in the paper. According to the image fuzzy entropy, the evaluation function of image segmentation is constructed in the first step. Then, the method adopts DE, the image fuzzy entropy parameter is regard as the initial population of individual. After the mutation, crossover and selection of three evolutionary processes to search for the maximum fuzzy entropy of parameters, the optimal threshold of the segmented gland is achieved. Finally, the mammary gland is segmented by the threshold method of maximum fuzzy entropy. Eight breast images with four tissue types are tested 100 times, with accuracy (Acc), sensitivity (Sen), specificity (Spe), positive predictive value (PPV), negative predicted value (NPV), and average structural similarity (Mssim) to measure the segmentation result. The Acc of the proposed algorithm is 98.46 ± 8.02E-03%, 95.93 ± 2.38E-02%, 93.88 ± 6.59E-02%, 94.73 ± 1.82E-01%, 96.19 ± 1.15E-02%, and 97.51 ± 1.36E-02%, 96.64 ± 6.35E-02%, and 94.76 ± 6.21E-02%, respectively. The mean Mssim values of the 100 tests were 0.985, 0.933, 0.924, 0.907, 0.984, 0.928, 0.938, and 0.941, respectively. Our proposed algorithm is more effective and robust in comparison to the other fuzzy entropy based on swarm intelligent optimization algorithms. The experimental results show that the proposed algorithm has higher accuracy in the segmentation of mammary glands, and may serve as a gold standard in the analysis of treatment of breast tumors.

[In-Vivo Noninvasive Measurement of Human Blood Glucose Levels by Mid-Infrared Spectrograph with External CO(2) Laser Source].

Diabetes is a kind of diseases which does harm to people's health, and the detection of human blood glucose levels utilizing blood samples will result in pain even infection for patients. Thus the in-vivo noninvasive measurement of human blood glucose levels has vital value in clinical diagnosis, detection and therapy, and it also is a very hot research topic with challenging. At present, as to various noninvasive detection methods, the technology based on mid-infrared absorption spectrophotometry with ATR has been gaining increasing attention. However, when carrying out noninvasive measurement of human blood glucose levels by means of the spectrophotometry equipped with routine light sources, the penetration depth of probe light in human tissues is low and thus it is very difficult to reach the stromal layer containing body fluids and especially dermis layer containing blood for probe light, which resulting in low relativity between experimental data and real human blood glucose levels and thus limiting the clinical application. Generally, not only the mid-infrared laser with high strength and high purity can deeper penetrate the human tissues, but also the output wavelengths at 1 035 cm(-1) of CO2 laser very coincide with the fundamental frequency characteristic absorption at 1 029 cm(-1) of glucose. Thus, in this work, a novel noninvasive mid-infrared measurement system to detect human blood glucose levels has been successfully assembled, in which a CO2 laser was used a self-defined external light source of the new mid-infrared absorption spectrophotometry with ATR. In this system, the absorbance of human fingertip at 1 035 cm(-1) has been measured when external CO2 laser source was used as probe light, at the same time, the mid-infrared absorption spectra of fingertip have been also obtained and absorbance at 1 492 cm(-1) has been recorded. The human blood glucose levels were determined synchronously by means of the routine medical method. The experimental results showed that the ratio in fingertip between absorbance at 1 035 cm(-1) from the laser source and one at 1 492 cm(-1) from mid-infrared absorption spectrophotometry could synchronously change with the human blood glucose levels, and the ratio presents certain positive relativity with the real human blood glucose levels(R=0. 812 5). Thus the measurement data could be used as a new index of blood glucose level in human body, which showed the potential in clinical diagnosis of the ATR mid-infrared absorption spectrophotometry with external CO(2) laser source in noninvasive measurement of human blood glucose levels.